University Taster
Economics – University Taster
5.2 Multiple Linear Regression
Multiple linear regression (MLR) extends simple linear regression to model the relationship between one dependent variable and multiple independent variables. It is widely used in econometrics, business analytics, and social sciences to identify trends and make predictions, helping to interpret complex data and inform decision-making.
Application of Multiple Linear Regression
MLR can be used to examine how various factors such as education level, years of work experience, and industry type collectively impact an individual's salary. Alternatively, it can assess how variables like advertising expenditure, pricing strategies, and market competition affect a company's sales revenue. This ability to incorporate multiple predictors enables researchers to capture the complexity of real-world scenarios more effectively.
Tip
In MLR, you are dealing with multiple variables at once, which can be hard to conceptualise. Always visualise your data with scatter plots or 3D graphs (when possible) to get an intuitive understanding of how the variables are related. This can help you better interpret your model’s results.
Below is a graph showing how the data is collected using a 3D graph, with three different variables:
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